Showing 3 open source projects for "genetic algorithm cuda"

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    HIPAcc

    HIPAcc

    Heterogeneous Image Processing Acceleration (HIPACC) Framework

    HIPAcc development has moved to github: https://github.com/hipacc HIPAcc allows to design image processing kernels and algorithms in a domain-specific language (DSL). From this high-level description, low-level target code for GPU accelerators is generated using source-to-source translation. As back ends, the framework supports CUDA, OpenCL, and Renderscript. HIPAcc allows programmers to develop imaging applications while providing high productivity, flexibility and portability as well as competitive performance: the same algorithm description serves as basis for targeting different GPU accelerators and low-level languages.
    Downloads: 0 This Week
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  • 2

    VolTK

    A Lightweighted Toolkit For Volume Rendering

    A Lightweighted Toolkit For Volume Rendering Project Started by Fei Yang Provide both CPU based and GPU (CUDA) based volume rendering. See http://www.fei-yang.org/?page_id=12 for complete descriptions and package downloads VolTK is a free C++ Toolkit that implements a tri-layer volume rendering framework, which is designed to meet the requirements of both algorithm research and application assemblage. Features * Tri-layer volume rendering * CPU implementation: multi-threading supported * GPU implementation: CUDA based implementation * CPU-GPU correspondance * Both low level interfaces and high level interfaces are provided * Replace the components easily with your own design * Various rendering modes: MIP/Isosurface/Full volume rendering * Endoscopy interaction mode implemented * Pre-integration supported * Cross platform (windows and RHEL tested)
    Downloads: 0 This Week
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  • 3
    Moved to github! https://github.com/aaronbot3000/image-evolver The goal of the Image Evolver is to recreate a source picture using overlapping transparent shapes positioned a genetic algorithm.
    Downloads: 0 This Week
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